Customized ranking by user preference using LRR model
Chiang, Bo-Yu
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https://hdl.handle.net/2142/78480
Description
Title
Customized ranking by user preference using LRR model
Author(s)
Chiang, Bo-Yu
Issue Date
2015-04-24
Department of Study
Computer Science
Discipline
Computer Science
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
M.S.
Degree Level
Thesis
Keyword(s)
Latent Aspect Rating Analysis (LARA)
Recommendation system
Abstract
In this thesis, we proposed a customized ranking system that can rank all the entities given a specific user preference. Rank entities by user’s preference is an inevitable strategy of saving user’s time browsing and extracting useful
information from Internet. Modern websites always rank these entities by a single numeric value computed by averaging overall rating, but this ranking scheme is of limited use to users.
With di↵erent aspect preference, it is obvious that the restaurants ranking
should be di↵erent based on their famous features, e.g., service, environment, price. We used the LRR (Latent Rating Regression) model to aggregate restaurants aspect score and proposed two ranking approaches. The experiment
results show that the two ranking approaches are both better than the
baseline ranking approach.
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